‘The other right’: control strategies and the role of language use in laparoscopic training
Bibliographic record
Abstract
CONTEXT: Laparoscopic techniques present a particular challenge to the academic surgeon in maintaining control and patient safety. The authors explored the use of verbal and physical control strategies including deixis, language used to locate subject in spatio-temporal, social and discoursal contexts, in this setting. METHODS: Forty cases of laparoscopic cholecystectomy at an academic centre were video and audio-recorded. Surgeon and trainee discourses and physical gestures during the crucial anatomical steps of the operation were qualitatively analysed using a hybrid inductive and deductive technique with explicit attention to the use of deixis. RESULTS: Laparoscopic surgeon educators use verbal and physical strategies and engage in bidirectional communication to maintain indirect control of an operation where direct control is not possible. Among verbal strategies, deictic language predominates. DISCUSSION: As in open surgery, laparoscopic surgical educators attempt to exert control over surgical procedures when the instruments are in the hands of a trainee. One dominant strategy is the use of deictic language, which may be ambiguous. In addition to the physical manoeuvres and bidirectional communication used to disambiguate, instructors must attend to potential uncertainties and explicitly clarify frames of reference in order to enhance educational experiences and maximise patient safety.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".